To investigate differences in pathogenesis, diagnosis and resistance pathways between HIV-1 subtypes, an accurate subtyping tool for large datasets is needed. We aimed to evaluate the performance of automated subtyping tools to classify the different subtypes and circulating recombinant forms using pol, the most sequenced region in clinical practice. We also present the upgraded version 3 of the Rega HIV subtyping tool (REGAv3). HIV-1 pol sequences (PR+RT) for 4674 patients retrieved from the Portuguese HIV Drug Resistance Database, and 1872 pol sequences trimmed from full-length genomes retrieved from the Los Alamos database were classified with statistical-based tools such as COMET, jpHMM and STAR; similarity-based tools such as NCBI and Stanford; and phylogenetic-based tools such as REGA version 2 (REGAv2), REGAv3, and SCUEAL. The performance of these tools, for pol, and for PR and RT separately, was compared in terms of reproducibility, sensitivity and specificity with respect to the gold standard which was manual phylogenetic analysis of the pol region. The sensitivity and specificity for subtypes B and C was more than 96% for seven tools, but was variable for other subtypes such as A, D, F and G. With regard to the most common circulating recombinant forms (CRFs), the sensitivity and specificity for CRF01_AE was ~99% with statistical-based tools, with phylogenetic-based tools and with Stanford, one of the similarity based tools. CRF02_AG was correctly identified for more than 96% by COMET, REGAv3, Stanford and STAR. All the tools reached a specificity of more than 97% for most of the subtypes and the two main CRFs (CRF01_AE and CRF02_AG). Other CRFs were identified only by COMET, REGAv2, REGAv3, and SCUEAL and with variable sensitivity. When analyzing sequences for PR and RT separately, the performance for PR was generally lower and variable between the tools. Similarity and statistical-based tools were 100% reproducible, but this was lower for phylogenetic-based tools such as REGA (~99%) and SCUEAL (~96%). REGAv3 had an improved performance for subtype B and CRF02_AG compared to REGAv2 and is now able to also identify all epidemiologically relevant CRFs. In general the best performing tools, in alphabetical order, were COMET, jpHMM, REGAv3, and SCUEAL when analyzing pure subtypes in the pol region, and COMET and REGAv3 when analyzing most of the CRFs. Based on this study, we recommend to confirm subtyping with 2 well performing tools, and be cautious with the interpretation of short sequences.

Understanding HIV-1 subtype distribution and epidemiology can assist preventive measures and clinical decisions. Sequence variation may affect antiviral drug resistance development, disease progression, evolutionary rates and transmission routes.

Bacterial endospores are the most resistant cell type known to humans, as they are able to withstand extremes of temperature, pressure, chemical injury, and time. They are also of interest because the endospore is the infective particle in a variety of human and livestock diseases. Endosporulation is characterized by the morphogenesis of an endospore within a mother cell. Based on the genes known to be involved in endosporulation in the model organismBacillus subtilis, a conserved core of about 100 genes was derived, representing the minimal machinery for endosporulation. The core was used to define a genomic signature of about 50 genes that are able to distinguish endospore-forming organisms, based on complete genome sequences, and we show this 50-gene signature is robust against phylogenetic proximity and other artifacts. This signature includes previously uncharacterized genes that we can now show are important for sporulation inB. subtilisand/or are under developmental control, thus further validating this genomic signature. We also predict that a series of polyextremophylic organisms, as well as several gut bacteria, are able to form endospores, and we identified 3 new loci essential for sporulation inB. subtilis:ytaF,ylmC, andylzA. In all, the results support the view that endosporulation likely evolved once, at the base of theFirmicutesphylum, and is unrelated to other bacterial cell differentiation programs and that this involved the evolution of new genes and functions, as well as the cooption of ancestral, housekeeping functions.

Human immunodeficiency virus type 1 (HIV-1) genetic diversity, due to its high evolutionary rate, has long been identified as a main cause of problems in the development of an efficient HIV-1 vaccine. However, little is known about differences in evolutionary rate between different subtypes. In this study, we collected representative samples of the main epidemic subtypes and circulating recombinant forms (CRFs), namely, sub-subtype A1, subtypes B, C, D, and G, and CRFs 01_AE and 02_AG. We analyzed separate data sets for pol and env . We performed a Bayesian Markov chain Monte Carlo relaxed-clock phylogenetic analysis and applied a codon model to the resulting phylogenetic trees to estimate nonsynonymous (dN) and synonymous (dS) rates along each and every branch. We found important differences in the evolutionary rates of the different subtypes. These are due to differences not only in the dN rate but also in the dS rate, varying in roughly similar ways, indicating that these differences are caused by both different selective pressures (for dN rate) and the replication dynamics (for dS rate) (i.e., mutation rate or generation time) of the strains. CRF02_AG and subtype G had higher rates, while subtype D had lower dN and dS rates than the other subtypes. The dN/dS ratio estimates were also different, especially for the env gene, with subtype G showing the lowest dN/dS ratio of all subtypes.

In recent years, an increasing number of outbreaks of Dengue, Chikungunya and Zika viruses have been reported in Asia and the Americas. Monitoring virus genotype diversity is crucial to understand the emergence and spread of outbreaks, both aspects that are vital to develop effective prevention and treatment strategies. Hence, we developed an efficient method to classify virus sequences with respect to their species and sub-species (i.e. serotype and/or genotype). This ArboTyping tool provides an easy-to-use software implementation of this new method and was validated on a large dataset assessing the classification performance with respect to whole-genome sequences and partial-genome sequences. Available online: http://krisp.ukzn.ac.za/app/. Dengue (DENV), Chikungunya (CHIKV) and Zika (ZIKV) are considered major public health challenges. In addition to the epidemic caused by DENV, which has been described in many tropical countries, the introduction of CHIKV and ZIKV in these countries is a major public health concern. These arboviruses are primarily transmitted by mosquitoes of the species Ae. Aegypti and its related diseases result in increased financial costs associated with diagnosis and treatment. To support the design of efficient diagnosis, prevention and treatment strategies, a bioinformatics tool has been developed for the genotyping of these viruses based on appropriate evolutionary models in an automatic, accurate and rapid manner. A set of virus reference sequences was obtained from GenBank and used for the development of the tools. This process involved the alignment of the reference sequences followed by phylogenetic tree reconstructions. To assign the genotypes uploaded by the user, the tool analyses the sequences one by one, genotypes through identification, alignment and phylogenetic reconstruction. This computational method allows the high-throughput classification of these virus species and genotypes in seconds. As shown experimentally, genotypes are classified most confidently using the envelope gene or complete genome sequences.

Human immunodeficiency virus type 1 (HIV-1) is classified in nine subtypes (A to D, F, G, H, J, and K), a number of subsubtypes, and several circulating recombinant forms (CRFs). Due to the high level of genetic diversity within HIV-1 and to its worldwide distribution, this classification system is widely used in fields as diverse as vaccine development, evolution, epidemiology, viral fitness, and drug resistance. Here, we demonstrate how the high recombination rates of HIV-1 may confound the study of its evolutionary history and classification. Our data show that subtype G, currently classified as a pure subtype, has in fact a recombinant history, having evolved following recombination between subtypes A and J and a putative subtype G parent. In addition, we find no evidence for recombination within one of the lineages currently classified as a CRF, CRF02_AG. Our analysis indicates that CRF02_AG was the parent of the recombinant subtype G, rather than the two having the opposite evolutionary relationship, as is currently proposed. Our results imply that the current classification of HIV-1 subtypes and CRFs is an artifact of sampling history, rather than reflecting the evolutionary history of the virus. We suggest a reanalysis of all pure subtypes and CRFs in order to better understand how high rates of recombination have influenced HIV-1 evolutionary history.